code: def test_resnet(self, name, resnet_cls):
      x = objax.random.normal((4, 3, 128, 128))
      model = resnet_cls(in_channels=3, num_classes=10)
      # run in eval mode
      y_eval = model(x, training=False)
      self.assertEqual(y_eval.shape, (4, 10))
      # run in train mode
      y_eval = model(x, training=True)
      self.assertEqual(y_eval.shape, (4, 10))
  
file_path: objax/tests/resnet_v2.py
imports: import unittest
  from parameterized import parameterized
  from functools import partial
  import numpy
  import tensorflow
  import objax
  from objax.zoo.resnet_v2 import ResNet18, ResNet34, ResNet50, ResNet101, ResNet152, ResNet200
  from objax.zoo.resnet_v2 import convert_keras_model, load_pretrained_weights_from_keras
label_desc: Use image node_id 1 for calling the TestResNetV2 obj's underlying member method code with example usage: obj.test_resnet(name, resnet_cls) without return types